3D-CNN and Autoencoder-Based Gas Detection in Hyperspectral Images

The detection of gas emission levels is a crucial problem for ecology and human health. Hyperspectral image analysis offers many advantages over traditional gas detection systems with its detection capability from safe distances. Observing that the existing hyperspectral gas detection methods in the...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE journal of selected topics in applied earth observations and remote sensing Vol. 16; pp. 1474 - 1482
Main Authors:	Ozdemir, Okan Bilge, Koz, Alper
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Ablation Artificial neural networks Autoencoders Classification Convolutional neural networks convolutional neural networks (CNNs) Deep learning Detection gas detection Gases Hyperspectral imaging hyperspectral unmixing Image analysis Image processing Infrared radiation Machine learning Methods Neural networks Pixels Radiance Sulfur Sulfur dioxide Sulphur Sulphur dioxide Target detection Temperature data Temperature distribution Three-dimensional displays Trigonometric functions
ISSN:	1939-1404, 2151-1535
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!